Logistic Regression Model to Investigate the Risk Factors for Glaucoma

Abstract

Many studies have found that age, race, gender, past family history, and intraocular pressure (IOP) of the eyes are key risk factors for glaucoma disease. The current study aims to evaluate the relationship between glaucoma and various glaucoma risk factors in the Arabian ethnicity using a cohort cross-sectional observational design. Therefore, the current study is targeted at building a regression model to estimate the probability of injury to glaucoma disease, which is one of the serious diseases that affect the eyes. It uses the logistic regression model, which is one of the modern non parametric methods, and a cohort cross-sectional observational design. The study included a total of 136 glaucoma patients. The findings show that there is no link between gender and glaucoma (p = 0.202), while there is a link between age and glaucoma (p = 0.004). Furthermore, the findings demonstrate that there is no association between diabetic mellitus (DM) and glaucoma (p = 0.273), although there is a relationship between hypertension and healing degree (p = 0.035) and diabetes and healing degree (p = 0.001). The findings also show that the factors affecting injury are: age, gender, pressure, and geographical location, and that diabetes and climatic factors are not influential. Current findings may aid in the development of intervention strategies that will raise glaucoma awareness in the future.